gusucode.com > 扩展卡尔曼滤波，粒子滤波，去偏卡尔曼滤波和循环增益尔曼滤波的源程序 > 循环增益卡尔曼滤波/new_err_count.m

    %由各次的误差计算出目标的平均误差，作为跟踪的均值估计，然后根据均值估计得出方差估计
function [ME_final_view_err_x,ME_final_filter_err_x,ME_final_view_err_y,ME_final_filter_err_y,RMSE_final_view_err_x,RMSE_final_filt_err_x,RMSE_final_view_err_y,RMSE_final_filt_err_y]=new_err_count(ME_temp_view_err_x,ME_temp_filter_err_x,ME_temp_view_err_y,ME_temp_filter_err_y);
[ROW,COL]=size(ME_temp_view_err_x);
for i=1:COL
    ME_final_view_err_x(i)=sum(ME_temp_view_err_x(:,i))/ROW;
    ME_final_filter_err_x(i)=sum(ME_temp_filter_err_x(:,i))/ROW;
    ME_final_view_err_y(i)=sum(ME_temp_view_err_y(:,i))/ROW;
    ME_final_filter_err_y(i)=sum(ME_temp_filter_err_y(:,i))/ROW;
end
for i=1:COL
    RMSE_final_view_err_x(i)=sum((ME_temp_view_err_x(:,i)-ME_final_view_err_x(i)*ones(ROW,1)).^2)/ROW;
    RMSE_final_filt_err_x(i)=sum((ME_temp_filt_err_x(:,i)-ME_final_filt_err_x(i)*ones(ROW,1)).^2)/ROW;
    RMSE_final_view_err_y(i)=sum((ME_temp_view_err_y(:,i)-ME_final_view_err_y(i)*ones(ROW,1)).^2)/ROW;
    RMSE_final_filt_err_y(i)=sum((ME_temp_filt_err_y(:,i)-ME_final_filt_err_y(i)*ones(ROW,1)).^2)/ROW;
end